[lines=2]AUTOMATIC modulation classification (AMC) is a vital technique to identify the modulation formats under noise and interference [1]}. AMC has been widely used in military and civilian applications, such as spectrum management, electronic warfare, interference identification [2]}, [3]}. The AMC schemes mainly have two categories, namely, model-driven AMC and data-driven AMC. The model-driven schemes can be mainly include likelihood-based (LB) schemes and feature-based (FB) schemes [1]}. The LB schemes can obtain the optimal solution from the Bayes’ sense by calculating the likelihood function under the modulation hypothesis. The FB schemes aim to find better features and have lower complexity with robust performances.
